Greedy Algorithm Based Load Optimization of Peak and Valley Electricity Prices for Smart Communities

The problem of “load optimization” in intelligent communities has always been a complex problem that troubles the industry. To deal with this issue, this paper proposes a peak valley price based on a Greedy algorithm to optimize a load of smart communities, aiming to achieve load optimization while obtaining benefits. Therefore, firstly, the load distribution characteristics of the smart community were studied, and load distribution and charging probability of different electric vehicle users were obtained based on the orderly charging framework of the community electric vehicles. Secondly, the peak valley price model based on the Greedy algorithm was constructed. Finally, under this model, the daily load of Shanghai Smart Community is selected for analysis, experimental calculations were conducted using residential time-of-use electricity prices as the data basis, and the results of the examples verified that this method has good optimization and economic efficiency for a load of intelligent residential areas.